The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
00:35:13 · Rory O'Driscoll, Jason Lemkin, Harry Stebbings
[00:35:13] S1: And in fact, as I looked at this data, which one of my colleagues was doing for something else, I think what I actually realized you need to do is then you say, if you extrapolate, what level of growth are you assuming to make this math work? Because yes, Jason, are. Because every year, I mean, every decade, it looks bigger than the last decade with the exception of 1970s because stocks go up. But the question is, I mean, made a comment for 25,000,000,000 plus outcomes and in a world per fund, yeah, and there are only 130 above 10,000,000,000 ever. So there's probably only 70 above 25. And so you got to get four new ones. It's doable, but you can't miss a lot here, dude. [00:35:52] S0: But that's what Andreessen got so right. People, when we started our investment, maybe pre my investing career, but people mocked Andreessen in the early days for overpaying and doing this wrong and saying, we have to be in all the winners. And they just did the math. Yes, you have to be in all the winners. And even a lot of the winners, won't make money in because you'll overpay, but the super winners will make up for all of it. It's it's just basic. And everyone... All the Yahoos mocked them, they are completely right. The price of overpaying for a winner is get... Being in the super winner. [00:36:19] S2: Well, of super winners, Jason, do [00:36:21] S1: you wanna come back to
00:36:21 · Rory O'Driscoll, Harry Stebbings, Jason Lemkin
[00:36:21] S1: you wanna come back to [00:36:22] S2: the investment committee? We can do a deep mind. Damas the legend that is Damas Esarbus, raised at about $10,000,000,000, give or take, from Thrive a matter of months ago. Now Isomorphic Labs, his company, in talks to raise it between 40 to $50,000,000,000 price. We can do this? [00:36:41] S0: I mean, generational talent has generational prices today. As much as I believe in the JEV teams and the TypeSafe teams, he's gonna pull together a team like never been seen since the dawn of mankind in artificial intelligence. Maybe he fails. Maybe he's had enough of it. Maybe he's enjoyed life in London too much, too many posh clubs. But I think I've seen the fire. It is a scary bet. We have our liquidation preference, and no one will be able to assemble a set of talent like this. This is the next and last chance to cherry pick the best of the best of the best, and this is the job.
00:37:10 · Rory O'Driscoll
[00:37:10] S1: The interesting thing about this company will be that unlike the vast bulk of the revenues that come from the foundation models, where it's, you know, intelligence automation, where the value capture is replaced labor. Here, the value capture is not replaced labor. It's actually make science discoveries. And the way because you know, when you discover it, when you do a molecule, if you automate the 500,000,000 of science spend that you pay science wages to, that's not really going to cut it. What you really want to do is, know, when you create the $200,000,000,000 drug, you want to get 10% of that on a royalty basis. So it's kind of the as the models devour all the knowledge worker dollars that are available to them in terms of direct replacement, at some point, they're going to have to monetize via creating whole new things with their intelligence. And, you know, it's a lot more credible today just given the math, the recent work they did on math, which as one mathematician correctly pointed out, don't actually get paid a whole ton for solving Stokes, Navia, whatever it is. But if you can discover the next GLP drug, that's a winner, because those things do money. So it will be interesting to see I have in the past said it's hard to get the drug companies to extract meaningful royalties when they still got to do phase one, phase two, phase three. And many of these companies end up being drug companies down the line. It'll be interesting to see what happens here, but it's a big pile of money if you can extract the value, not just from a labor percentage.
00:38:34 · Jason Lemkin, Harry Stebbings
[00:38:34] S0: No, no, I think we're all going to be on 10 GLP-one like drugs in a few years. And I think, you know, we never really got the full story on Anthropix wet lab. I think the potential here is even greater than is let on. I think the potential for drug discovery is probably massive. And we're going from weirdos microdosing to finding out we're all going to have a set of drugs that dramatically extend longevity and quality of life. And they can radically accelerate it, own the IP, and have other people do the hard work, maybe AI really can reboot the entire industry fairly rapidly. Of course, not all of it, not the trials, not the rest, but man, if you could get a GLP-one out five years faster. [00:39:11] S2: Jason, do you actually buy that? I don't mean that cynically. [00:39:14] S0: The drug stuff? Yeah. Yeah. Only very recently did I buy it. I thought it was wackos and Brian Johnson's and people selling crap. [00:39:21] S2: What caused you to change your mindset?
00:39:21 · Harry Stebbings, Jason Lemkin, Rory O'Driscoll
[00:39:21] S2: What caused you to change your mindset? [00:39:22] S0: Because the the medical evidence for GLP ones is so... It's so profound. It's so for heart disease, for so many other things. And I think our ability to tailor drugs to extend longevity is the massive market. It's better than inference. You know, and if you talk to any just physicians at the cutting edge now, they're all saying to anybody like your hip or whatever, just don't hurt the other one. Like, just get there. Like in another couple of years, the amount of longevity we're gonna able to achieve is so much higher that I just think the wackos of the microdosers of SF and Brian Johnson made me skeptical, but just the overwhelming evidence of the benefits that almost everyone should be on the GLP-one, right? And the fact that we're going to get better and better at figuring all this stuff out. I mean, we're just walking sets of cancer and heart disease and other things that having material impacts will radically extend longevity, radically extend longevity. [00:40:14] S1: There's a whole sequence of steps before you even have adequately good molecule identification with some understanding of how it works, and then you still have all the different biophases. So as I say, I do believe it'll be harder to capture value than you think, but I'm really glad they're trying. Guys, I wanna talk
00:40:14 · Rory O'Driscoll, Harry Stebbings
[00:40:14] S1: There's a whole sequence of steps before you even have adequately good molecule identification with some understanding of how it works, and then you still have all the different biophases. So as I say, I do believe it'll be harder to capture value than you think, but I'm really glad they're trying. Guys, I wanna talk [00:40:29] S2: about one which may be a little bit earlier than usual, but we have Mecca, which is the MACRA or the surge for robotics data, physical world data that can be implemented in most often robotics. Raises 60,000,000 series b from Sequoia. The reason I wanted to bring it up is that, you know, we have micro AGI in Europe, which has posted race to a 100,000,000 very quickly. There's Macca, which is well over 100,000,000 in ARR. There's another provider that I'm forgetting the name of, XOFT or XO Soft or whatever it is, that's again over 100. And we just see the sheer volume of data providers over 100,000,000. What should we read, infer, analyze from this?